We recently demonstrated that ultra-high-speed real-time fMRI using multi-slab echo-volumar imaging (MEVI) significantly increases sensitivity for mapping task-related activation and resting-state networks (RSNs) compared to echo-planar imaging (Posse et al., 2012). In the present study we characterize the sensitivity of MEVI for mapping RSN connectivity dynamics, comparing independent component analysis (ICA) and a novel seed-based connectivity analysis (SBCA) that combines sliding-window correlation analysis with meta-statistics. This SBCA approach is shown to minimize the effects of confounds, such as movement, and CSF and white matter signal changes, and enables real-time monitoring of RSN dynamics at time scales of tens of seconds. We demonstrate highly sensitive mapping of eloquent cortex in the vicinity of brain tumors and arterio-venous malformations, and detection of abnormal resting-state connectivity in epilepsy. In patients with motor impairment, resting-state fMRI provided focal localization of sensorimotor cortex compared with more diffuse activation in task-based fMRI. The fast acquisition speed of MEVI enabled segregation of cardiac-related signal pulsation using ICA, which revealed distinct regional differences in pulsation amplitude and waveform, elevated signal pulsation in patients with arterio-venous malformations and a trend toward reduced pulsatility in gray matter of patients compared with healthy controls. Mapping cardiac pulsation in cortical gray matter may carry important functional information that distinguishes healthy from diseased tissue vasculature. This novel fMRI methodology is particularly promising for mapping eloquent cortex in patients with neurological disease, having variable degree of cooperation in task-based fMRI. In conclusion, ultra-high-real-time speed fMRI enhances the sensitivity of mapping the dynamics of resting-state connectivity and cerebro-vascular pulsatility for clinical and neuroscience research applications.

In many superconducting transition-edge sensor (TES) microcalorimeters, the measured electrical noise exceeds theoretical estimates based on a thermal model of a single body thermally connected to a heat bath. Here, we report on noise and complex impedance measurements of a range of designs of TESs made with a Mo/Au bilayer. We have fitted the measured data using a two-body model, where the x-ray absorber and the TES are connected by an internal thermal conductance G ae . We find that the so-called excess noise measured in these devices is consistent with the noise generated from the internal thermal fluctuations between the x-ray absorber and the TES. Our fitted parameters are consistent with the origin of G ae being from the finite thermal conductance of the TES itself. These results suggest that even in these relatively low resistance Mo/Au TESs, the internal thermal conductance of the TES may add significant additional noise and could account for all the measured excess noise. Furthermore, we find that around regions of the superconducting transition with rapidly changing derivative of resistance with respect to temperature, an additional noise mechanism may dominate. These observations may lead to a greater understanding of TES devices and allow the design of TES microcalorimeters with improved performance.

Future X-ray astrophysics experiments require multiplexed readout of high fill-factor, kilo-pixel arrays of transitionedge sensors (TESs), with very high spectral resolution over a broad range of energies. In this paper we report on a prototype kilo-pixel array of Mo/Au TESs readout with 8-column by 32-row time-division multiplexing (TDM). This system is being used to demonstrate the critical detector and readout technology for ESA's Athena X-IFU, and when complete will be used in laboratory astrophysics experiments. Our array and TDM readout have demonstrated a combined full-width-at-half-maximum energy resolution, including > 200 pixels, of: 1.95 eV for Ti-Kα (4.5 keV), 1.97 eV for Mn-Kα (5.9 keV), 2.16 eV for Co-Kα (6.9 keV), 2.33 eV for Cu-Kα (8 keV), 3.26 eV for Br-Kα (11.9 keV). The 1 sigma statistical errors are ≤0.01 eV for all spectra. These results meet the broad-band resolution requirements for X-IFU with margin.